Research on granular computing approach in rough set

被引：0
|
作者：
Dai, Jin [1 ]
Hu, Feng [2 ]
Yan, Yi [1 ]
机构：
[1] School of Software Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China
[2] College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China
来源：
International Journal of Signal Processing, Image Processing and Pattern Recognition | 2014年 / 7卷 / 06期
关键词：
Attribute reduction - Complex problems - Effective tool - Equivalence relations - Evidence theories - Fuzzy information processing - Massive data - Research fields;
D O I：
10.14257/ijsip.2014.7.6.08
中图分类号：
学科分类号：
摘要：
Granulation of information appears in many areas, such as machine learning, evidence theory, and data mining. Granular computing is the core research field in granulation of information. It is an effective tool for complex problem, massive data mining and fuzzy information processing. In the basis of principle of granularity, we aim to study the granular decomposing method in granules space based on rough set. Moreover, the criteria conditions for attribution necessity and attribute reduction are proposed. Finally, the corresponding equivalence is proved to traditional rough set theory. It will lay the foundation for attribute reduction under the granular representation in rough set. © 2014 SERSC.
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页码：85 / 94
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